Architect/Director - AI/ML & Healthcare Analytics

Job Title: Director/Architect AI/ML & Healthcare Analytics

About WhiteSpace Health(an Omega Healthcare company) (WSH) -https://whitespacehealth.com

About the Role

Director – AI/ML & Healthcare Analytics

healthcare analytics

Key Responsibilities

AI Strategy & Vision

• Define and lead the enterprise

  AI/ML and healthcare analytics strategy

  , aligned to RCM modernization and business goals.
• Develop scalable predictive and prescriptive analytics models for denials, collections, AR forecasting, payer behavior, underpayments, and operational optimization.
• Utilize AI/ML to uncover

  dead-value opportunities

  , revenue leakages, and inefficiencies across the RCM lifecycle.
• Drive the creation of reusable AI microservices, decisioning engines, and next-gen analytics capabilities for the product platform

AI/ML Product Development

• Architect and build scalable, production-grade AI/ML solutions across ingestion, modeling, deployment, monitoring, and continuous improvement.
• Lead the modernization of the AI stack to support multi-cloud (Azure, AWS, GCP) environments using containerized and cloud-native services.
• Own the end-to-end lifecycle of AI/ML models—data preparation, feature engineering, training, evaluation, deployment, and monitoring.

Advanced Automation & AI Operations

• Drive AI-enabled automation that improves throughput, reduces manual dependency, and boosts operational efficiency.
• Implement MLOps best practices—automated pipelines, model versioning, testing, retraining, and drift detection.
• Integrate AI into CI/CD processes and product release workflows to support rapid experimentation and deployment.

GenAI Innovation

• Build GenAI solutions for automated documentation, summarization, knowledge extraction, IDP, and conversational RCM assistants.
  • Implement LLM-powered quality checks, intelligent test generation, predictive denials and payment models, coding/charge-capture AI, and NLP-driven claims automation. • Use embeddings, vector databases, RAG, and multimodal models to boost accuracy, data quality, and user experience.

Data Integrity & Modernization

• Oversee data readiness for AI use cases—data architecture, governance, feature stores, and cloud-based data pipelines.
• Guide the transition to modern data platforms supporting streaming, real-time analytics, and large-scale ML workloads.

Business Value & Analytics

• Derive measurable business value through AI-driven automation, insights, and predictive capabilities.
• Build ROI models, value frameworks, and AI impact dashboards to track efficiency gains, cost reduction, and revenue lift.
• Partner with Product and Operations to ensure AI investments translate directly into customer and business outcomes.

Leadership & Collaboration

• Build and mentor a high-performing AI/ML team of engineers, researchers, data scientists, and applied ML practitioners.
• Work cross-functionally with Engineering, Cloud, QA, Product, Operations, and Client Services to embed AI into product and business workflows.
• Influence executive stakeholders through clear communication, strategic planning, and strong execution excellence.

Qualifications

Must Have

• 15+ years of experience in Data Science / AI / ML with at least 5+ years in leadership roles.
• Proven track record building and deploying ML and AI solutions at scale in production.
• Deep experience with healthcare datasets, RCM workflows, payer/provider data, and compliance constraints.
• Expertise with ML frameworks (TensorFlow, PyTorch, Scikit-learn), LLMs, NLP, and cloud AI services.
• Experience in GenAI, LLM fine-tuning, RAG systems, or document intelligence.
• Strong understanding of ETL/ELT pipelines, data engineering, and distributed systems.
• Strong hands-on engineering capability with Python, SQL, cloud-native pipelines, and distributed computing.
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI, Airflow).
• Demonstrated business acumen with ability to quantify AI impact and drive strategy.

Nice to Have

• Familiarity with healthcare interoperability standards (FHIR, HL7, X12).
• Experience in multi-cloud orchestration and modern data platforms.
• Experience with vector databases, embeddings, document intelligence, or multimodal AI solutions.

Attributes

• Strong strategic thinking coupled with deep technical hands-on ability.
• Highly analytical, creative, and results-oriented with a passion for innovation.
• Ability to influence diverse stakeholders and drive cross-functional programs.
• Ownership mindset with a continuous improvement and experimentation culture.
• Deep understanding of ethical AI, fairness, privacy, and compliance in healthcare.